From the 1 of 5 linked papers with an AI index.
5 papers
A fast summation method for the DFT-D3 dispersion correction
Victoria Valeeva, Cheuk Hin Ho, Mario Geiger +4
The paper introduces FourierD3, a low‑rank decomposition technique that restores separability in the DFT‑D3 dispersion correction, enabling fast particle‑mesh evaluation in O(N log…
Flexible Uncertainty Calibration for Machine-Learned Interatomic Potentials
Cheuk Hin Ho, Christoph Ortner, Yangshuai Wang
Reliable uncertainty quantification (UQ) is essential for developing machine-learned interatomic potentials (MLIPs) in predictive atomistic simulations. Conformal prediction (CP) i…
An Atomic Cluster Expansion Potential for Twisted Multilayer Graphene
Yangshuai Wang, Drake Clark, Sambit Das +5
Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machi…
A foundation model for atomistic materials chemistry
Ilyes Batatia, Philipp Benner, Yuan Chiang +85
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much…
Many-Body Coarse-Grained Molecular Dynamics with the Atomic Cluster Expansion
Yangshuai Wang, Gabor Csanyi, Christoph Ortner
Molecular dynamics (MD) simulations provide detailed insight into atomic-scale mechanisms but are inherently restricted to small spatio-temporal scales. Coarse-grained molecular dy…